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Bistability and oscillations in co‐repressive synthetic microbial consortia

Overview of attention for article published in Quantitative Biology, March 2017
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Title
Bistability and oscillations in co‐repressive synthetic microbial consortia
Published in
Quantitative Biology, March 2017
DOI 10.1007/s40484-017-0100-y
Pubmed ID
Authors

Mehdi Sadeghpour, Alan Veliz‐Cuba, Gábor Orosz, Krešimir Josić, Matthew R. Bennett

Abstract

Synthetic microbial consortia are conglomerations of multiple strains of genetically engineered microbes programmed to cooperatively bring about population-level phenotypes. By coordinating their activity, the constituent strains can display emergent behaviors that are difficult to engineer into isogenic populations. To do so, strains are engineered to communicate with one another through intercellular signaling pathways. As a result, the regulatory networks that control gene transcription throughout the population are sensitive to the extracellular concentration of the signaling molecules, and hence the relative densities of constituent strains. Here, we use computational modeling to examine how the behavior of a synthetic microbial consortium results from the interplay between the population dynamics governed by cell growth and the internal transcriptional dynamics governed by cell-to-cell signaling. Specifically, we examine a synthetic microbial consortium in which two strains each produce signals that down-regulate transcription in the other. Within a single strain this regulatory topology is called a "co-repressive toggle switch" and can lead to bistability. We find that in a two-strain synthetic microbial consortium the existence and stability of different states depends on the population-level dynamics of the interacting strains. As the two strains passively compete for space within the colony, their relative fractions can fluctuate and thus alter the strengths of intercellular signals. These fluctuations can drive the consortium to alternative equilibria. Additionally, if the growth rates of the strains depend on their transcriptional states, an additional feedback loop is created that can generate relaxation oscillations. These findings demonstrate that the dynamics of microbial consortia cannot be predicted from their regulatory topologies alone, but also is determined by interactions between the strains.

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 36%
Researcher 8 16%
Student > Doctoral Student 4 8%
Other 2 4%
Professor > Associate Professor 2 4%
Other 3 6%
Unknown 13 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 26%
Agricultural and Biological Sciences 11 22%
Engineering 4 8%
Environmental Science 1 2%
Nursing and Health Professions 1 2%
Other 3 6%
Unknown 17 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2017.
All research outputs
#20,200,306
of 24,833,004 outputs
Outputs from Quantitative Biology
#72
of 89 outputs
Outputs of similar age
#245,373
of 316,457 outputs
Outputs of similar age from Quantitative Biology
#5
of 5 outputs
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